What are the methods for sorting in pandas

The pandas sorting methods are: 1. Use the sort_values() method; 2. Use the sort_index() method; 3. Use the order() method; 4. Use the sort() method; 5. Use nlargest() and nsmallest() method, etc. Detailed introduction: 1. Use the sort_values() method to sort data frames or Series objects. It can be sorted by multiple columns, and supports ascending and descending sorting, etc.

The operating system for this tutorial: Windows 10 system, DELL G3 computer.

Pandas is a popular Python data analysis library that provides a variety of sorting methods. The following are common methods for sorting using Pandas:

1. Use the sort_values() method

The sort_values() method is used to sort data frames or Series objects. It can sort by multiple columns and supports ascending and descending sorting.

Sample code:

import pandas as pd  
  
df = pd.DataFrame({'A': [3, 1, 2], 'B': [1, 2, 3]})  
df_sorted = df.sort_values(by='A', ascending=False)  # 按列A进行降序排序

2. Use the sort_index() method

The sort_index() method is used to sort the index of a data frame or Series object. It sorts in ascending order by default and supports sorting by multiple index levels.

Sample code:

import pandas as pd  
  
df = pd.DataFrame({'A': [3, 1, 2], 'B': [1, 2, 3]}, index=['c', 'a', 'b'])  
df_sorted = df.sort_index()  # 按索引升序排序

3. Use the order() method

The order() method is used to sort data frames or Series objects. It sorts in ascending order by default and supports sorting by multiple columns.

Sample code:

import pandas as pd  
  
df = pd.DataFrame({'A': [3, 1, 2], 'B': [1, 2, 3]})  
df_sorted = df.order(by='A')  # 按列A进行升序排序

4. Use the sort() method

The sort() method is used to sort Series objects. It sorts in ascending order by default and supports sorting by multiple values.

Sample code:

import pandas as pd  
  
s = pd.Series([3, 1, 2])  
s_sorted = s.sort()  # 对Series对象进行升序排序

5. Use the nlargest() and nsmallest() methods

nlargest() and nsmallest() methods are used to obtain data frames or Series objects respectively. The largest n values ​​and the smallest n values ​​in . They can be sorted by multiple columns and support sorting by absolute size.

Sample code:

import pandas as pd  
  
df = pd.DataFrame({'A': [3, 1, 2], 'B': [1, -2, 3]})  
df_sorted = df.nlargest(2, columns='B')  # 按列B获取最大的两个值，并返回包含它们的行

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